2 citations · 3 across the 17 of their papers we have counts for
17 papers
OmniStepBench: Deployment-Aware Agent Evaluation across Modalities and Task Complexity
Yu Liu, Zhilin Liu, Zhiwei Yang +7
As large language models evolve from question-answering systems into general-purpose agents, evaluation must move beyond static answer correctness to assess multimodal perception,…
CARE: Pre-Execution Command Verification for Shell-Executing LLM Agents
Yu Liu, Wenxiao Zhang, Zhiwei Yang +7
Large Language Model (LLM) agents are increasingly used for coding and terminal automation, making shell-command dispatch a high-stakes runtime control point. We study command-leve…
MOF-Sleuth: Tool-Grounded Reward Alignment for Explainable Fine-Grained MOF CIF Auditing
Yu Liu, Zhiwei Yang, Diandian Guo +7
Large metal-organic framework (MOF) databases support simulation, screening, and machine learning through crystallographic information files (CIFs). Subtle chemical and structural…
When the Same Musical Knowledge Forgets Differently: A Clean Probe of Pathway-Dependent Forgetting
Yu Liu, Zhiwei Yang, Wenxiao Zhang +8
A model can learn that the piano piece Für Elise is calm and reflective by listening to the audio or by reading a text description, but does it matter which route that knowledge to…
Trans-RAG: Query-Centric Vector Transformation for Secure Cross-Organizational Retrieval
Yu Liu, Kun Peng, Wenxiao Zhang +4
Retrieval Augmented Generation (RAG) systems deployed across organizational boundaries face fundamental tensions between security, accuracy, and efficiency. Current encryption meth…
STIndex: A Context-Aware Multi-Dimensional Spatiotemporal Information Extraction System
Wenxiao Zhang, Yu Liu, Qiang sun +5
Extracting structured knowledge from unstructured data still faces practical limitations: entity and event extraction pipelines remain brittle, knowledge graph construction require…
Dialogue Model Optimization via Agent Game and Adaptive Tree-based GRPO
Kun Peng, Conghui Tan, Yu Liu +7
Open-ended dialogue agents aim to deliver engaging, personalized interactions by adapting to users' traits, but existing methods face critical limitations: over-reliance on pre-col…
Does Faithfulness-Guided Alignment Hurt Accuracy? Unlocking Accurate and Faithful Post-Retrieval Reasoning
Yu Liu, Wenxiao Zhang, Diandian Guo +6
Retrieval-augmented generation (RAG) can achieve strong answer accuracy on multi-hop questions, but outcome-level rewards often leave reasoning traces weakly grounded and difficult…
PRISMA: Reinforcement Learning Guided Two-Stage Policy Optimization in Multi-Agent Architecture for Open-Domain Multi-Hop Question Answering
Yu Liu, Wenxiao Zhang, Cong Cao +10
Answering real-world open-domain multi-hop questions over massive corpora is a critical challenge in Retrieval-Augmented Generation (RAG) systems. Recent research employs reinforce…
MuVaC: A Variational Causal Framework for Multimodal Sarcasm Understanding in Dialogues
Diandian Guo, Fangfang Yuan, Cong Cao +5
The prevalence of sarcasm in multimodal dialogues on the social platforms presents a crucial yet challenging task for understanding the true intent behind online content. Comprehen…
Emotion Transfer with Enhanced Prototype for Unseen Emotion Recognition in Conversation
Kun Peng, Cong Cao, Hao Peng +5
Current Emotion Recognition in Conversation (ERC) research follows a closed-domain assumption. However, there is no clear consensus on emotion classification in psychology, which p…
Dialogues Aspect-based Sentiment Quadruple Extraction via Structural Entropy Minimization Partitioning
Kun Peng, Cong Cao, Hao Peng +5
Dialogues Aspect-based Sentiment Quadruple Extraction (DiaASQ) aims to extract all target-aspect-opinion-sentiment quadruples from a given multi-round, multi-participant dialogue.…
OPERA: A Reinforcement Learning--Enhanced Orchestrated Planner-Executor Architecture for Reasoning-Oriented Multi-Hop Retrieval
Yu Liu, Yanbing Liu, Fangfang Yuan +6
Recent advances in large language models (LLMs) and dense retrievers have driven significant progress in retrieval-augmented generation (RAG). However, existing approaches face sig…
T-T: Table Transformer for Tagging-based Aspect Sentiment Triplet Extraction
Kun Peng, Chaodong Tong, Cong Cao +6
Aspect sentiment triplet extraction (ASTE) aims to extract triplets composed of aspect terms, opinion terms, and sentiment polarities from given sentences. The table tagging method…
Multi-View Incongruity Learning for Multimodal Sarcasm Detection
Diandian Guo, Cong Cao, Fangfang Yuan +5
Multimodal sarcasm detection (MSD) is essential for various downstream tasks. Existing MSD methods tend to rely on spurious correlations. These methods often mistakenly prioritize…
Can Multimodal Large Language Model Think Analogically?
Diandian Guo, Cong Cao, Fangfang Yuan +4
Analogical reasoning, particularly in multimodal contexts, is the foundation of human perception and creativity. Multimodal Large Language Model (MLLM) has recently sparked conside…
RDGCN: Reinforced Dependency Graph Convolutional Network for Aspect-based Sentiment Analysis
Xusheng Zhao, Hao Peng, Qiong Dai +5
Aspect-based sentiment analysis (ABSA) is dedicated to forecasting the sentiment polarity of aspect terms within sentences. Employing graph neural networks to capture structural pa…